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Henry I. Miller and S. Stanley Young

In order to reduce the diversity gap between men and women and among various subpopulations represented in clinical trials, and to moderate the costs of these studies, we need to innovate in trial design. In other words, we need to think outside the box.

The design, execution, and analysis of clinical trials has become so complex that even for huge multinational drug companies with vast R&D experience, bringing a new medicine to market on average takes 12-15 years and costs well over a billion dollars. The increasing promise of personalized medicine–“the right drug for the right patient at the right time”--notwithstanding, the development of a new medicine is generally focused on the ultimate marketing to a broad range of people. (Examples include drugs like statins, anti-hypertensives, antibiotics, pain relievers and sleep-inducers, for example.)

However, there is wide variation in the responses of different subpopulations to certain drugs; for example, BiDil, a combination drug for congestive heart failure, is approved specifically for black patients (although it can be prescribed “off-label” for anyone).

There are wide differences in the ability of various ethnic groups and individuals to clear medications from the bloodstream because of heterogeneity in the activity of the enzymes that metabolize drugs. For that reason, drug safety and efficacy are affected by the variability in the genes that code for these enzymes.

This phenomenon is important because (with the exception of drugs that must be converted in the body from an inactive to an active form) individuals with low-metabolizing enzymes clear certain drugs slowly and have more medication in their blood for longer periods than those with high-metabolizing ones.

Aging causes important differences in responses to drugs; for several reasons, older patients are far more likely to experience adverse drug reactions. For one thing, clearance by the kidneys and liver, the two most important routes for the elimination of drugs, is reduced; as people age, these organs get less blood flow and there is diminished activity of the hepatic enzymes that metabolize drugs.

Another interesting age-related anomaly concerns the decrease in total body water and the relative increase in body fat seen in older people. Also, women have a higher percentage of body fat than men. Because of these differences, in the elderly of both sexes and in women, water-soluble drugs become more concentrated in the blood and fat-soluble drugs have longer half-lives.

These phenomena have critical implications for the clinical testing of new drugs for safety and efficacy. For example, if investigators perform a successful clinical trial that includes only men aged 20-50, how do we know whether it will be safe and effective for children, women and the elderly at the dose(s) tested? The short answer is, we don’t. We rely on post-marketing trials and surveillance to ascertain how widely applicable the data from the clinical trials are.

The obvious solution might seem to be simply to include in trials a cross-section of men and women; the young, middle-aged and elderly; and various major ethnic groups. In fact, in a garbled letter to the director of the National Institutes of Health, 22 Democratic members of Congress recently requested information about “NIH’s commitment to providing the data necessary to allow researchers to query all studies on ClinicalTrials.gov by sex and demographic data in order to advance the health of all citizens and address continuing issues with the participation of women and minorities in clinical trials.” They cited as a model the mandate of the NIH Revitalization Act of 1993, which requires that “women and minorities be included in all NIH-funded clinical trials in a manner sufficient to elicit information about individuals of both sexes/genders and diverse racial and ethnic groups and, particularly in NIH-defined Phase III clinical trials, to examine differential effects on such groups.”

Fortunately, that law has not been enforced because with current clinical trial design, those requirements could cause NIH-funded clinical research to grind to a virtual halt. If applied to R&D performed by the private sector, they could push development costs into the stratosphere and seriously impede the development of new drugs.

Consider that some “named” diseases, such as Alzheimer’s disease, autism or Non-Alcoholic Fatty Liver Disease probably represent a variety of pathological processes that cannot be differentiated with available diagnostic methods. Current clinical trial strategies are seldom designed to yield sound data for multiple etiologies or subgroups. Just testing men and women separately would require a doubling of the size of current clinical trials, and with additional test groups, the number of strata in a trial could easily spiral out of sight, making it unlikely that there would be sufficient numbers in each stratum for statistically significant estimations of safety and efficacy.

The reason is that the number of strata in a trial is the arithmetic product of the number of levels in each stratum, so that if groups were stratified according to the two sexes, four age ranges, three ethnicities and three etiologies, that would give us 2 x 4 x 3 x 3 = 72 strata. Such a study could require huge numbers of subjects in order to obtain sufficient statistical power to demonstrate an effect of the drug.

If we really want to fine-tune the design of clinical trials for a variety of sub-populations, we will need to think outside the box.

One intriguing possibility is what FDA calls an “adaptive design clinical study,” defined as one that “includes a prospectively planned opportunity for modification of one or more specified aspects of the study design and hypotheses based on analysis of data (usually interim data) from subjects in the study.” This is intended to “make the studies more efficient (e.g., shorter duration, fewer patients), more likely to demonstrate an effect of the drug if one exists, or more informative (e.g., by providing broader dose-response information).”

Another approach is what is called a “large, simple, randomized trial,” in which large numbers of patients (often in the tens of thousands) are recruited and the number of individual procedures–lab tests, scans, electrocardiograms and the like--is greatly reduced. The trials need to be large to have sufficient statistical power to detect only moderate effects, and must be simple to keep costs manageable. Such trials need to have easily determined, definitive endpoints, such as myocardial infarction, death, or the presence of an infection, and they work best for common diseases. In this model, patient entry requirements are greatly reduced in order to get a large, diverse patient population, monitoring is less intensive than in traditional trials, and much of it is performed by community physicians in their quotidian practice of medicine instead of in university medical centers.

An early example was the testing of the Salk polio vaccine in the early 1950’s, the trials of which were performed on about 600,000 children. Another was the UK’s Heart Protection Study, the initial results of which were published in 2002. It was the largest trial on record of cholesterol-lowering therapy and antioxidant vitamin supplementation in people at increased risk of heart disease. More than 20,000 individuals were randomized according to various prior conditions (coronary or other occlusive arterial disease, diabetes and hypertension) or other categories (women, elderly, and people with "low" cholesterol levels). It found that simvastatin (brand name, Zocor) could significantly reduce the risk of cardiovascular events but that vitamins had little effect.